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Proceedings Paper

Computationally efficient Bayesian tracking
Author(s): Jason Aughenbaugh; Brian La Cour
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Paper Abstract

In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.

Paper Details

Date Published: 10 May 2012
PDF: 14 pages
Proc. SPIE 8407, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, 840705 (10 May 2012); doi: 10.1117/12.919358
Show Author Affiliations
Jason Aughenbaugh, Univ. of Texas at Austin (United States)
Brian La Cour, Univ. of Texas at Austin (United States)


Published in SPIE Proceedings Vol. 8407:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012
Jerome J. Braun, Editor(s)

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